Crassulacean acid metabolism (CAM) is a water-use efficient adaptation of photosynthesis that has evolved independently many times in diverse lineages of flowering plants. We hypothesize that convergent evolution of protein sequence and temporal gene expression underpins the independent emergences of CAM from C3 photosynthesis. To test this hypothesis, we generate a de novo genome assembly and genome-wide transcript expression data for Kalanchoë fedtschenkoi, an obligate CAM species within the core eudicots with a relatively small genome (~260 Mb). Our comparative analyses identify signatures of convergence in protein sequence and re-scheduling of diel transcript expression of genes involved in nocturnal CO2 fixation, stomatal movement, heat tolerance, circadian clock, and carbohydrate metabolism in K. fedtschenkoi and other CAM species in comparison with non-CAM species. These findings provide new insights into molecular convergence and building blocks of CAM and will facilitate CAM-into-C3 photosynthesis engineering to enhance water-use efficiency in crops.

Already a proven mechanism for drought resilience, crassulacean acid metabolism (CAM) is a specialized type of photosynthesis that maximizes water-use efficiency by means of an inverse (compared to C 3 and C 4 photosynthesis) day/ night pattern of stomatal closure/opening to shift CO 2 uptake to the night, when evapotranspiration rates are low. A systems-level understanding of temporal molecular and metabolic controls is needed to define the cellular behaviour underpinning CAM. Here, we report high-resolution temporal behaviours of transcript, protein and metabolite abundances across a CAM diel cycle and, where applicable, compare the observations to the well-established C 3 model plant Arabidopsis. A mechanistic finding that emerged is that CAM operates with a diel redox poise that is shifted relative to that in Arabidopsis. Moreover, we identify widespread rescheduled expression of genes associated with signal transduction mechanisms that regulate stomatal opening/closing. Controlled production and degradation of transcripts and proteins represents a timing mechanism by which to regulate cellular function, yet knowledge of how this molecular timekeeping regulates CAM is unknown. Here, we provide new insights into complex post-transcriptional and -translational hierarchies that govern CAM in Agave. These data sets provide a resource to inform efforts to engineer more efficient CAM traits into economically valuable C 3 crops.T he water-use efficiency of Agave spp. hinges on crassulacean acid metabolism (CAM), a specialized mode of photosynthesis that evolved from ancestral C 3 photosynthesis in response to water and CO 2 limitation 1 and is found in ∼6.5% of higher plants. Whereas C 3 photosynthesis produces a three-carbon (3-C) molecule for carbon fixation during the day, CAM generates a four-carbon organic acid from carbon fixation at night. In CAM, this nocturnal carboxylation reaction is catalysed by phosphoenolpyruvate carboxylase (PEPC), and the 3-C substrate phosphoenolpyruvate (PEP) is supplied by the glycolytic breakdown of carbohydrate formed during the previous day. The nocturnally accumulated malic acid is stored overnight in a central vacuole, and during the subsequent day malate is decarboxylated to release CO 2 at an elevated concentration for Rubisco in the chloroplast. The diel separation of carboxylases in CAM is accompanied by an inverse (compared with C 3 and C 4 photosynthesis-performing species) day/night pattern of stomatal closure/ opening that results in improved water-use efficiency (CO 2 fixed per unit water lost) that is up to sixfold higher than that of C 3 photosynthesis plants and up to threefold higher than that of C 4 photosynthesis plants under comparable conditions 2 .The frequent emergence of CAM from C 3 photosynthesis throughout evolutionary history implies that all of the enzymes required for CAM are homologues of ancestral forms found in C 3 species 1,3 . As such, the CAM pathway has been identified as a target for synthetic biology because it offers the potential to engin...

BackgroundInduced resistance (IR) can be part of a sustainable plant protection strategy against important plant diseases. β-aminobutyric acid (BABA) can induce resistance in a wide range of plants against several types of pathogens, including potato infected with Phytophthora infestans. However, the molecular mechanisms behind this are unclear and seem to be dependent on the system studied. To elucidate the defence responses activated by BABA in potato, a genome-wide transcript microarray analysis in combination with label-free quantitative proteomics analysis of the apoplast secretome were performed two days after treatment of the leaf canopy with BABA at two concentrations, 1 and 10 mM.ResultsOver 5000 transcripts were differentially expressed and over 90 secretome proteins changed in abundance indicating a massive activation of defence mechanisms with 10 mM BABA, the concentration effective against late blight disease. To aid analysis, we present a more comprehensive functional annotation of the microarray probes and gene models by retrieving information from orthologous gene families across 26 sequenced plant genomes. The new annotation provided GO terms to 8616 previously un-annotated probes.ConclusionsBABA at 10 mM affected several processes related to plant hormones and amino acid metabolism. A major accumulation of PR proteins was also evident, and in the mevalonate pathway, genes involved in sterol biosynthesis were down-regulated, whereas several enzymes involved in the sesquiterpene phytoalexin biosynthesis were up-regulated. Interestingly, abscisic acid (ABA) responsive genes were not as clearly regulated by BABA in potato as previously reported in Arabidopsis. Together these findings provide candidates and markers for improved resistance in potato, one of the most important crops in the world.

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Metagenomic data from Obsidian Pool (Yellowstone National Park, USA) and 13 genome sequences were used to reassess genus-wide biodiversity for the extremely thermophilic The updated core genome contains 1,401 ortholog groups (average genome size for 13 species = 2,516 genes). The pangenome, which remains open with a revised total of 3,493 ortholog groups, encodes a variety of multidomain glycoside hydrolases (GHs). These include three cellulases with GH48 domains that are colocated in the glucan degradation locus (GDL) and are specific determinants for microcrystalline cellulose utilization. Three recently sequenced species, sp. strain Rt8.B8 (renamed here ), strain NA10 (renamed here ), and sp. strain Wai35.B1 (renamed here ), degraded Avicel and lignocellulose (switchgrass). was more efficient than in this regard and differed from the other 12 species examined, both based on genome content and organization and in the specific domain features of conserved GHs. Metagenomic analysis of lignocellulose-enriched samples from Obsidian Pool revealed limited new information on genus biodiversity. Enrichments yielded genomic signatures closely related to that of, but there was also evidence for other thermophilic fermentative anaerobes (, ,, and ). One enrichment, containing 89.8% and 9.7% , had a capacity for switchgrass solubilization comparable to that of These results refine the known biodiversity of and indicate that microcrystalline cellulose degradation at temperatures above 70°C, based on current information, is limited to certain members of this genus that produce GH48 domain-containing enzymes. The genus contains the most thermophilic bacteria capable of lignocellulose deconstruction, which are promising candidates for consolidated bioprocessing for the production of biofuels and bio-based chemicals. The focus here is on the extant capability of this genus for plant biomass degradation and the extent to which this can be inferred from the core and pangenomes, based on analysis of 13 species and metagenomic sequence information from environmental samples. Key to microcrystalline hydrolysis is the content of the glucan degradation locus (GDL), a set of genes encoding glycoside hydrolases (GHs), several of which have GH48 and family 3 carbohydrate binding module domains, that function as primary cellulases. Resolving the relationship between the GDL and lignocellulose degradation will inform efforts to identify more prolific members of the genus and to develop metabolic engineering strategies to improve this characteristic.

Biomass analysis is a slow and tedious process and not solely due to the long generation time for most plant species. Screening large numbers of plant variants for various geno-, pheno-, and chemo-types, whether naturally occurring or engineered in the lab, has multiple challenges. Plant cell walls are complex, heterogeneous networks that are difficult to deconstruct and analyze. Macroheterogeneity from tissue types, age, and environmental factors makes representative sampling a challenge and natural variability generates a significant range in data. Using high throughput (HTP) methodologies allows for large sample sets and replicates to be examined, narrowing in on more precise data for various analyses. This review provides a comprehensive survey of high throughput screening as applied to biomass characterization, from compositional analysis of cell walls by NIR, NMR, mass spectrometry, and wet chemistry to functional screening of changes in recalcitrance via HTP thermochemical pretreatment coupled to enzyme hydrolysis and microscale fermentation. The advancements and development of most high-throughput methods have been achieved through utilization of state-of-the art equipment and robotics, rapid detection methods, as well as reduction in sample size and preparation procedures. The computational analysis of the large amount of data generated using high throughput analytical techniques has recently become more sophisticated, faster and economically viable, enabling a more comprehensive understanding of biomass genomics, structure, composition, and properties. Therefore, methodology for analyzing large datasets generated by the various analytical techniques is also covered.

Plant root-associated microbial symbionts comprise the plant rhizobiome. These microbes function in provisioning nutrients and water to their hosts, impacting plant health and disease. The plant microbiome is shaped by plant species, plant genotype, soil and environmental conditions, but the contributions of these variables are hard to disentangle from each other in natural systems. We used bioassay common garden experiments to decouple plant genotype and soil property impacts on fungal and bacterial community structure in the Populus rhizobiome. High throughput amplification and sequencing of 16S, ITS, 28S and 18S rDNA was accomplished through 454 pyrosequencing. Co-association patterns of fungal and bacterial taxa were assessed with 16S and ITS datasets. Community bipartite fungal-bacterial networks and PERMANOVA results attribute significant difference in fungal or bacterial communities to soil origin, soil chemical properties and plant genotype. Indicator species analysis identified a common set of root bacteria as well as endophytic and ectomycorrhizal fungi associated with Populus in different soils. However, no single taxon, or consortium of microbes, was indicative of a particular Populus genotype. Fungal-bacterial networks were over-represented in arbuscular mycorrhizal, endophytic, and ectomycorrhizal fungi, as well as bacteria belonging to the orders Rhizobiales, Chitinophagales, Cytophagales, and Burkholderiales. These results demonstrate the importance of soil and plant genotype on fungal-bacterial networks in the belowground plant microbiome.

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes use of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. The resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.